Apple tightens App Store review guidelines targeting AI “nudify” & “bait-and-switch” apps

Apple has updated its App Store review guidelines to explicitly classify nonconsensual intimate imagery, including imagery produced with AI tools, as content that apps must proactively prevent and remove, according to an announcement published on the company's developer news page. The revision to guideline 1.2 extends existing content-moderation obligations, which already require apps hosting user-generated content to filter objectionable material, provide users a way to report offensive content, and allow users to block abusive accounts. Under the new wording, developers who fail to implement adequate safeguards, or who do not fix violations after being notified, risk breaching Apple's developer code of conduct and being removed from the App Store. Apple noted that pornographic material has long been banned on the platform, a category it says includes “nudification” apps that generate sexually explicit images of real people without their consent.

A second change, to guideline 2.5.19, addresses what Apple describes as bait-and-switch behavior: apps that misrepresent their purpose during review and then activate harmful capabilities only after approval. The guideline clarifies the company's longstanding prohibition on hidden or undocumented features and on apps that add functionality not present in the version submitted to review. Apple said apps found doing this are subject to removal from the App Store and expulsion from the Apple developer program.

In framing the update, Apple cited enforcement figures from the past year, saying it prevented more than 150,000 apps with safety issues from reaching customers and terminated over 193,000 developer accounts for fraud and abuse. The company attributed such violations to malicious actors, in some cases coordinated fraud operations, working to conceal harmful content until after approval, and said it continues to develop tools to detect that behavior faster. Apple said the revisions are intended to preserve user and developer trust as new risks and novel user experiences emerge.